Synthetic medical images can be generated with a StyleGAN and are indistinguishable from real data even by experts. However, the projection of real data via latent space onto a synthetic image shows clear deviations from the original (at least on the second image). This plays a major role especially when using GANs to perform tasks such as image correction (e.g. noise reduction), image interpolation or image interpretation by analyzing the latent space. Based on the results shown, it is highly recommended to perform an analysis of the projection accuracy before applying any of these applications.